Three machine learning techniques for automatic determination of rules to control locomotion

IEEE Transactions on Biomedical Engineering

Volumn 46, Issue 3, 1999, Pages 300-310

  Jonic, Slavica ^a   Jankovic, Tamara ^a   Gajic, Vladimir ^a   Popovic, Dejan ^a  

^a School of Electrical Engineering   (Serbia)

Author keywords

Adaptive network based fuzzy inference system (anfis); Artificial neural networks (ann's); Functional electrical stimulation (fes); Inductive learning (il); Multilayer perceptron; Radial basis function (rbf) ann; Walking

Indexed keywords

BACKPROPAGATION; COMPUTATIONAL COMPLEXITY; FUZZY SETS; INFERENCE ENGINES; LEARNING AIDS FOR HANDICAPPED PERSONS; LEARNING SYSTEMS; MOTION CONTROL; MULTILAYER NEURAL NETWORKS; MUSCLE; SENSORY PERCEPTION;

ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEM (ANFIS); INDUCTIVE LEARNING; RADIAL BASIS FUNCTION (RBF);

FUNCTIONAL ELECTRIC STIMULATION;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOMECHANICS; ELECTROSTIMULATION; ENTROPY; FLEXOR MUSCLE; KNEE; LOCOMOTION; WALKING;

ALGORITHMS; BIOMECHANICS; CLUSTER ANALYSIS; ENTROPY; FUZZY LOGIC; GAIT; HIP JOINT; HUMANS; KNEE JOINT; MODELS, BIOLOGICAL; MUSCLE, SKELETAL; NEURAL NETWORKS (COMPUTER); REFERENCE VALUES;

EID: 0033104629     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/10.748983     Document Type: Article

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